Diagnosing Visual Ignorance in Vision-Language Models
cs.CV, cs.LG
Submitted: 2026-06-05
Updated: 2026-09-27
Code: https://github.com/huggingface/accelerate
Terminology
Sources
- MIRAGE: The Illusion of Visual Understanding
- Qwen3-VL Technical Report
- Qwen2.5-VL Technical Report
- Eliciting Latent Predictions from Transformers with the Tuned Lens
- Sparse Autoencoders Find Highly Interpretable Features in Language Models
- Hidden in plain sight: VLMs overlook their visual representations
- BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain
- SEED-Bench: Benchmarking Multimodal LLMs with Generative Comprehension
- k-Sparse Autoencoders
- RePOPE: Impact of Annotation Errors on the POPE Benchmark
- Arbitration Failure, Not Perceptual Blindness: How Vision-Language Models Resolve Visual-Linguistic Conflicts
- DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
- Vision Language Models are Biased
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